Use of rapid small-scale column tests for simultaneous prediction of phosphorus and nitrogen retention in large-scale filters
MetadataShow full item record
StatisticsDisplay Item Statistics
CitationG. Ezzati, M.G. Healy, L. Christianson, K. Daly, O. Fenton, G. Feyereisen, S. Thornton, O. Callery, Use of rapid small-scale column tests for simultaneous prediction of phosphorus and nitrogen retention in large-scale filters, Journal of Water Process Engineering, Volume 37, 2020, 101473, ISSN 2214-7144, https://doi.org/10.1016/j.jwpe.2020.101473.
AbstractRapid small-scale column tests (RSSCTs) have been previously used to predict the effluent concentration of a single nutrient in large filters with good accuracy. However, in drainage waters originating from heavy textured soils, where there is a need for in-ditch filters to retain both dissolved reactive phosphorus (DRP) and ammonium (NH4) simultaneously, the suitability of a RSSCT approach to model both parameters must be proved. In this study, a decision support tool was used to identify appropriate media that may be placed in filters for the removal of DRP and NH4. The selected media for this study were sand and zeolite. Both media were placed in acrylic tubes each with an internal diameter of 0.01 m and with lengths ranging from 0.1 to 0.4 m, and their performance for simultaneous removal of DRP and NH4 (1 mg DRP and NH4-N L−1) from water was evaluated. The data generated from the RSSCTs were used to model DRP and NH4 removals in 0.4 m-long laboratory columns of internal diameter 0.1 m, which had the same media configuration as the small columns and were operated using the same influent concentrations. The developed model successfully predicted the effluent concentration of both the DRP and NH4-N from the large columns. This indicates using RSSCTs to model the performance of filters will produce substantial savings in operational, financial and labour costs, without affecting the accuracy of model predictions.
The following license files are associated with this item:
- Creative Commons
Except where otherwise noted, this item's license is described as © 2020 The Author(s). Published by Elsevier Ltd.